When an image is taken it can be blurred due to for example handshake or the like. If the point spread function (PSF) is known, a deconvolution method can be applied to the blurred image to restore the original image from the blurry one. However, with most image deconvolutions ringing artifacts occur as a side effect, in particular if the point spread function in the frequency domain has nulls.
Different approaches have been carried out to reduce ringing artifacts of image deconvolution. One approach proposes image deconvolution using natural image priors, i. e. the sparsity of image gradients. Besides the sparsity prior another approach suggests a local image prior, i. e. the local image variants. By means of two image priors the ringing artifact can be avoided in flat areas.
However, according to prior art there are methods that work well for some types of pictures, but fail for other kinds of pictures. For example there are methods which provide a good result in flat areas but encounter problems with texture areas in particular in regions where texture and strong image structure co-exist.